Healing of a Chronic Pressure Injury in a Patient Treated With Medical Cannabis for Pain and Sleep Improvement: A Case Report
Bibliographic record
Abstract
BACKGROUND: A small body of evidence suggests medical cannabis may facilitate wound healing, but the exact mechanism of this effect is unclear. PURPOSE: This case report describes a patient with a pressure injury (PI) who received cannabis oil treatment for pain management and sleep improvement. METHODS: A 37-year-old woman with multiminicore disease, scoliosis, short-chain acyl-CoA dehydrogenase deficiency, and epilepsy presented to the Neurology Centre of Toronto with chronic pain and sleep disturbance, including difficulty initiating and maintaining sleep. She also had a 5-year history of a PI between her right iliac crest and right rib cage that had progressively worsened. The patient received a medical cannabis oil protocol that used a combination of cannabidiol and tetrahydrocannabinol. RESULTS: Cannabis oil was effective in treating pain and sleep difficulties. Unexpectedly, during the first 2 weeks of treatment, the PI started to heal and was almost completely closed at the 2-month follow-up. CONCLUSION: Although it is unknown if the observed healing of this refractory PI was indirectly or directly related to the cannabidiol and tetrahydrocannabinol treatment, the potential relationships among pain, sleep disturbance, cannabis treatment, and healing should be explored.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".